Somnath Ghosh

About

Somnath Ghosh is the Michael G. Callas Chair Professor in the Department of Civil and Systems Engineering at Johns Hopkins University. He is the director of the Computational Mechanics Research Laboratory and the founding director of the Center for Integrated Structure-Materials Modeling and Simulations, an interdisciplinary research center dedicated to advancing computational structure-material analysis and design. Ghosh also serves as co-director of NASA’s Space Technology Research Institute for Model-based Qualification and Certification of Additive Manufacturing, where he leads the development of a digital twin for additive manufacturing. His research focuses on computational engineering and sciences that integrate computational mechanics and physics, with emphasis on multiscale modeling, structure-materials modeling and simulations, materials characterization, process modeling, machine learning, uncertainty quantification, additive manufacturing, and multi-physics modeling of multifunctional materials. Ghosh has made transformative contributions to modeling metals, composites, and multifunctional materials, particularly in the prognosis and life prediction of metals and composites, as well as in multifunctional applications such as damage sensing in piezo-electric materials and load-bearing antennas. His computational models and tools are widely used in aerospace, automotive, materials, and propulsion industries, including organizations like Pratt & Whitney, General…

Research topics

• Composite material
• Materials science
• Thermodynamics
• Computer Science
• Machine Learning
• Artificial Intelligence
• Physics
• Mechanics
• Chemistry
• Statistical physics

Selected publications

• A coupled crystal plasticity FEM and phase-field model for crack evolution in microstructures of 7000 series aluminum alloys

  Engineering Fracture Mechanics · 2020 · 58 citations

  Senior authorCorresponding
  DOI

• Machine Learning-Aided Parametrically Homogenized Crystal Plasticity Model (PHCPM) for Single Crystal Ni-Based Superalloys

  JOM · 2020 · 38 citations

  Senior authorCorresponding
  DOI

• Uncertainty-quantified parametrically homogenized constitutive models (UQ-PHCMs) for dual-phase α/β titanium alloys

  npj Computational Materials · 2020 · 38 citations

  Senior authorCorresponding

  Abstract This paper develops an uncertainty-quantified parametrically homogenized constitutive model (UQ-PHCM) for dual-phase α / β titanium alloys such as Ti6242S. Their microstructures are characterized by primary α -grains consisting of hcp crystals and transformed β -grains consisting of alternating laths of α ( hcp ) and β ( bcc ) phases. The PHCMs bridge length-scales through explicit microstructural representation in structure-scale constitutive models. The forms of equations are chosen t…

  DOI

• Generative adversarial network (GAN) enabled Statistically equivalent virtual microstructures (SEVM) for modeling cold spray formed bimodal polycrystals

  npj Computational Materials · 2024-02-07 · 22 citations

  articleOpen accessSenior authorCorresponding

  Abstract Image-based micromechanical models, necessary for the development of structure-property-response relations, are far from mature for complex microstructures with multi-modal distributions of morphological and crystallographic features, such as those occurring with cold spray-formed (CSF) aluminum alloys. These materials have a bimodal polycrystalline microstructure composed of recrystallized ultra-fine grains (UFGs) and deformed coarse grains (CGs) within prior particles. A prime reason…

  PublisherOA PDFDOI

• Machine learning-enabled multiscale modeling platform for damage sensing digital twin in piezoelectric composite structures

  Scientific Reports · 2025-02-24 · 18 citations

  articleOpen access1st authorCorresponding

  Nondestructive evaluation (NDE) of aerospace structures plays a crucial role in their successful operation under harsh environments. Most NDE methods, however, lack real-time in-situ predictive capabilities of evolving damage and are conducted in a post-mortem manner. This paper proposes a damage-sensing digital twin (DT) for piezoelectric composite structures incorporating microscale morphology and mechanisms into structural damage to address this shortcoming. The DT framework consists of a two…

  PublisherOA PDFDOI

Recent grants

• Integrated Experimental- Computational Modeling of Deformation and Fatigue in Advanced Structural Materials

  NSF · $246k · 2008–2011

• Multi-Scale Modeling and Multi-Objective Design Framework for Location-Specific Material Behavior in Additively Manufactured Components

  NSF · $515k · 2018–2022

• Atomistic Simulation Based Crack Evolution Models for Crystal Plasticity FEM of Crystalline Metals

  NSF · $302k · 2012–2016

Frequent coauthors

• Suresh Moorthy

  16 shared

• Jing Li

  Wuhan University of Technology

  15 shared

• Jiahao Cheng

  Oak Ridge National Laboratory

  13 shared

• Michael A. Groeber

  The Ohio State University

  13 shared

• Lichen Fang

  Johns Hopkins University

  12 shared

• Zeyu Zhu

  Dalian Jiaotong University

  12 shared

• Sung Hoon Kang

  Johns Hopkins University

  12 shared

• Frieder Mugele

  University of Twente

  12 shared

Awards & honors

• Theodore von Karman Medal by the American Society of Civil E…
• Elected to the European Academy of Sciences and Arts

Similar researchers at Johns Hopkins University

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• James Guesth-37
• Jochen Muellerh-32